Multi-Frame Blind Deconvolution Algorithms for Daylight and Strong Turbulence Imaging
National intelligence requirements for Space Situational Awareness (SSA) are hindered by the lack of a reliable capability to image satellites during the daytime hours with optical sensors. Presently, most optical SSA observations are conducted during terminator conditions i.e., morning or evening twilight when the sun illuminates the satellite, but not the observatory. There are two fundamental issues that make daytime imaging more technically challenging than terminator imaging: atmospheric seeing is generally worse during the day than during terminator; and high levels of background radiation due to scattered sunlight significantly lower the signal-to-noise ratio (SNR) of the measurements. This project proposes to build on previous MFBD algorithm experience and on current research being performed by PDS for daytime imaging systems in order to develop the mathematical basis for new MFBD approaches and constraints that are tailored to daylight imaging in the presence of strong turbulence. BENEFIT: Facility security and battlespace management rely heavily video surveillance systems. In daylight these systems are limited by the stron turbulance encountered over long path lengths. MFBD operating in such conditions can bring huge improvements to such applications. The market is estimated to be in billions of dollars. The development of the new MFBD methods proposed herein offers the potential to contribute to better ultrasound imaging and other applications in the medical imaging field.
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